Fit to spectra containing two Gaussian components and with noise varied from 1% to 30%. The upper frame shows the reduced χ² values for GaussPy (blue line) and SPIF (red line) fits. The crosses indicate cases where programs have preferred the single-component fit. Some GaussPy fits have failed, and in those cases no χ² value is plotted. In the case of GaussPy, we modelled the parameter using smoothing parameters α ~ δv for noise ≤ 16% and α ~ 40 × δv for noise > 16%. A fixed smoothing parameter for varying noise levels prevents GaussPy from isolating the multiple components. In the case of SPIF, both one-and two-component fits were performed and the model with the lower AIC values is included in the figure. The lower frame shows one example where GaussPy (blue line) has opted for a single-component fit, resulting in a noticeably higher χ¹ value in frame a.